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feat(build): migrate from Prettier to Oxfmt for performant code formatting (#42434)
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@@ -5,13 +5,13 @@ sidebar_position: 1
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version: 1
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---
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import useBaseUrl from "@docusaurus/useBaseUrl";
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import useBaseUrl from '@docusaurus/useBaseUrl';
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## Creating Your First Dashboard
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This section is focused on documentation for end-users who will be using Superset
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for the data analysis and exploration workflow
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(data analysts, business analysts, data
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(data analysts, business analysts, data
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scientists, etc).
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:::tip
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@@ -37,22 +37,44 @@ pre-configured in Superset for you.
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Under the **+** menu in the top right, select Data, and then the _Connect Database_ option:
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<img src={useBaseUrl("/img/tutorial/tutorial_01_add_database_connection.png")} width="600" />{" "} <br/><br/>
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<img
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src={useBaseUrl('/img/tutorial/tutorial_01_add_database_connection.png')}
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width="600"
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/>
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<br />
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<br />
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Then select your database type in the resulting modal:
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<img src={useBaseUrl("/img/tutorial/tutorial_02_select_database.png" )} width="600" />{" "} <br/><br/>
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<img
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src={useBaseUrl('/img/tutorial/tutorial_02_select_database.png')}
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width="600"
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/>
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<br />
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<br />
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Once you've selected a database, you can configure a number of advanced options in this window,
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or for the purposes of this walkthrough, you can click the link below all these fields:
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<img src={useBaseUrl("/img/tutorial/tutorial_03a_database_connection_string_link.png" )} width="600" />{" "} <br/><br/>
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<img
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src={useBaseUrl(
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'/img/tutorial/tutorial_03a_database_connection_string_link.png',
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)}
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width="600"
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/>
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<br />
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<br />
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Please note, if you are trying to connect to another locally running database (whether on host or another container), and you get the message `The port is closed.`, then you need to adjust the HOST to `host.docker.internal`
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Once you've clicked that link you only need to specify two things (the database name and SQLAlchemy URI):
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<img src={useBaseUrl("/img/tutorial/tutorial_03b_connection_string_details.png" )} width="600" />{" "} <br/><br/>
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<img
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src={useBaseUrl('/img/tutorial/tutorial_03b_connection_string_details.png')}
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width="600"
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/>
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<br />
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<br />
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As noted in the text below the form, you should refer to the SQLAlchemy documentation on
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[creating new connection URIs](https://docs.sqlalchemy.org/en/12/core/engines.html#database-urls)
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@@ -70,28 +92,28 @@ that you want exposed in Superset for querying.
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Navigate to **Data ‣ Datasets** and select the **+ Dataset** button in the top right corner.
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<img src={useBaseUrl("/img/tutorial/tutorial_08_sources_tables.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_08_sources_tables.png')} />
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A modal window should pop up in front of you. Select your **Database**,
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**Schema**, and **Table** using the drop downs that appear. In the following example,
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we register the **cleaned_sales_data** table from the **examples** database.
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<img src={useBaseUrl("/img/tutorial/tutorial_09_add_new_table.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_09_add_new_table.png')} />
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To finish, click the **Add** button in the bottom right corner. You should now see your dataset in the list of datasets.
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### Customizing column properties
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Now that you've registered your dataset, you can configure column properties
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for how the column should be treated in the Explore workflow:
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for how the column should be treated in the Explore workflow:
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- Is the column temporal? (should it be used for slicing & dicing in time series charts?)
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- Should the column be filterable?
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- Is the column dimensional?
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- If it's a datetime column, how should Superset parse
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the datetime format? (using the [ISO-8601 string pattern](https://en.wikipedia.org/wiki/ISO_8601))
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the datetime format? (using the [ISO-8601 string pattern](https://en.wikipedia.org/wiki/ISO_8601))
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<img src={useBaseUrl("/img/tutorial/tutorial_column_properties.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_column_properties.png')} />
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### Superset semantic layer
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@@ -99,53 +121,55 @@ Superset has a thin semantic layer that adds many quality of life improvements f
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The Superset semantic layer can store 2 types of computed data:
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1. Virtual metrics: you can write SQL queries that aggregate values
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from multiple column (e.g. `SUM(recovered) / SUM(confirmed)`) and make them
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available as columns for (e.g. `recovery_rate`) visualization in Explore.
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Aggregate functions are allowed and encouraged for metrics.
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from multiple column (e.g. `SUM(recovered) / SUM(confirmed)`) and make them
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available as columns for (e.g. `recovery_rate`) visualization in Explore.
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Aggregate functions are allowed and encouraged for metrics.
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<img src={useBaseUrl("/img/tutorial/tutorial_sql_metric.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_sql_metric.png')} />
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You can also certify metrics if you'd like for your team in this view.
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1. Virtual calculated columns: you can write SQL queries that
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customize the appearance and behavior
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of a specific column (e.g. `CAST(recovery_rate as float)`).
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Aggregate functions aren't allowed in calculated columns.
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customize the appearance and behavior
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of a specific column (e.g. `CAST(recovery_rate as float)`).
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Aggregate functions aren't allowed in calculated columns.
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<img src={useBaseUrl("/img/tutorial/tutorial_calculated_column.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_calculated_column.png')} />
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### Creating charts in Explore view
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Superset has 2 main interfaces for exploring data:
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- **Explore**: no-code viz builder. Select your dataset, select the chart,
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customize the appearance, and publish.
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customize the appearance, and publish.
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- **SQL Lab**: SQL IDE for cleaning, joining, and preparing data for Explore workflow
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We'll focus on the Explore view for creating charts right now.
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To start the Explore workflow from the **Datasets** tab, start by clicking the name
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of the dataset that will be powering your chart.
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<img src={useBaseUrl("/img/tutorial/tutorial_launch_explore.png" )} /><br/><br/>
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<img src={useBaseUrl('/img/tutorial/tutorial_launch_explore.png')} />
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<br />
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<br />
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You're now presented with a powerful workflow for exploring data and iterating on charts.
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- The **Dataset** view on the left-hand side has a list of columns and metrics,
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scoped to the current dataset you selected.
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scoped to the current dataset you selected.
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- The **Data** preview below the chart area also gives you helpful data context.
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- Using the **Data** tab and **Customize** tabs, you can change the visualization type,
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select the temporal column, select the metric to group by, and customize
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the aesthetics of the chart.
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select the temporal column, select the metric to group by, and customize
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the aesthetics of the chart.
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As you customize your chart using drop-down menus, make sure to click the **Run** button
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to get visual feedback.
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<img src={useBaseUrl("/img/tutorial/tutorial_explore_run.jpg" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_explore_run.jpg')} />
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In the following screenshot, we craft a grouped Time-series Bar Chart to visualize
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our quarterly sales data by product line just by clicking options in drop-down menus.
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<img src={useBaseUrl("/img/tutorial/tutorial_explore_settings.jpg" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_explore_settings.jpg')} />
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### Creating a slice and dashboard
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@@ -156,26 +180,32 @@ To save your chart, first click the **Save** button. You can either:
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In the following screenshot, we save the chart to a new "Superset Duper Sales Dashboard":
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<img src={useBaseUrl("/img/tutorial/tutorial_save_slice.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_save_slice.png')} />
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To publish, click **Save and goto Dashboard**.
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Behind the scenes, Superset will create a slice and store all the information needed
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to create your chart in its thin data layer
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(the query, chart type, options selected, name, etc).
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(the query, chart type, options selected, name, etc).
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<img src={useBaseUrl("/img/tutorial/tutorial_first_dashboard.png" )} style={{width: "100%", maxWidth: "500px"}} />
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<img
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src={useBaseUrl('/img/tutorial/tutorial_first_dashboard.png')}
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style={{ width: '100%', maxWidth: '500px' }}
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/>
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To resize the chart, start by clicking the Edit Dashboard button in the top right corner.
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To resize the chart, start by clicking the Edit Dashboard button in the top right corner.
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<img src={useBaseUrl("/img/tutorial/tutorial_edit_button.png" )} width="300" />
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<img src={useBaseUrl('/img/tutorial/tutorial_edit_button.png')} width="300" />
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Then, click and drag the bottom right corner of the chart until the chart layout snaps
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into a position you like onto the underlying grid.
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<img src={useBaseUrl("/img/tutorial/tutorial_chart_resize.png" )} style={{width: "100%", maxWidth: "500px"}} />
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<img
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src={useBaseUrl('/img/tutorial/tutorial_chart_resize.png')}
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style={{ width: '100%', maxWidth: '500px' }}
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/>
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Click **Save** to persist the changes.
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Click **Save** to persist the changes.
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Congrats! You’ve successfully linked, analyzed, and visualized data in Superset. There are a wealth
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of other table configuration and visualization options, so please start exploring and creating
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@@ -192,14 +222,14 @@ Non-owner users access can be managed in two different ways. The dashboard needs
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- Granting a role access to a dashboard will bypass dataset level checks. Having dashboard access implicitly grants read access to all the featured charts in the dashboard, and thereby also all the associated datasets.
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- If no roles are specified for a dashboard, regular **Dataset permissions** will apply.
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<img src={useBaseUrl("/img/tutorial/tutorial_dashboard_access.png" )} />
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<img src={useBaseUrl('/img/tutorial/tutorial_dashboard_access.png')} />
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### Publishing a Dashboard
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If you would like to make your dashboard available to other users, click on the `Draft` button next to the
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title of your dashboard.
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<img src={useBaseUrl("/img/tutorial/publish_button_dashboard.png" )} />
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<img src={useBaseUrl('/img/tutorial/publish_button_dashboard.png')} />
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:::warning
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Draft dashboards are only visible to the dashboard owners and admins. Published dashboards are visible to all users with access to the underlying datasets or if RBAC is enabled, to the roles that have been granted access to the dashboard.
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